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Record W4238077954 · doi:10.32920/ryerson.14652684

Strategic adsorption/desorption of cellulases NS 50013 onto/from AVICEL PH 101 and protobind 1000

2021· preprint· en· W4238077954 on OpenAlexaffabout
Khurram Shahzad Baig

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicBiofuel production and bioconversion
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsCellulaseAdsorptionDesorptionCelluloseChemistryMicrocrystalline celluloseHydrolysisStrawLigninChromatographyNuclear chemistryChemical engineeringOrganic chemistryInorganic chemistry

Abstract

fetched live from OpenAlex

Desorption of active cellulases from lignocellulosic substrates is a potential technique to reuse cellulases for the production of bioethanol. For desorption studies, adsorption of cellulases had to be performed first. Adsorption of cellulases NS 50013 onto microcrystalline cellulose (Avicel PH 101) and wheat straw lignin (Protobind 1000) was studied. It was found that Protobind adsorbed twice the amount of cellulases than Avicel did. An adsorption strategy developed was to work at pH 5 and a temperature less than 323 K to get maximum adsorption on the cellulose component, less adsorption on the lignin component of lignocellulosic materials, and to harmonize adsorption temperature with the industrial hydrolysis situation. Desorption of cellulases from Avicel and Protobind over a range of 298 K to 343 K and a pH of 6 to 9 was studied. Desorption obtained at pH 9 and 333K was optimum for both Avicel and Protobind. Hence, desorption was enhanced by 21 % and 11% for Avicel and Protobind respectively. The cellulases activity for Avicel was 48 FPU mL-1 at pH 9, 333 K, 5% glycerol, representing 91 % of the initial activity and for Protobind, the activity was 33 FPU mL-1 which represents about 66 % of the initial activity. All of these values were higher than ever reported in literature. At pH 5 and 298 K the amount of cellulases desorbed from untreated wheat straw (WS) was 33 % of those initially used for the adsorption step. It was increased to 42 % when 30 % delignified WS was used, and was further increased to 48 % for 60 % delignified WS. Desorption obtained for 60 % delignified WS was 75 % at pH 9, 333K and 5% glycerol. The desorption strategy recommended for bioethanol producing industries, is: 1) removal of lignin; 2) adsorption of cellulases at pH 5 and lower than 323K; 3) hydrolysis of lignocellulosic material; and 4) desorption of cellulases from non-hydrolyzed material at 333 K, pH 9, with 5-10 % glycerol. The proposed strategic desorption of cellulases may reduce the cost of Canadian bioethanol production by 26.5 % due to 75 % recyclability of active cellulases.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.023
GPT teacher head0.215
Teacher spread0.191 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes2
Has abstractyes

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